perf: use lighter topic model

server/app.py

@@ -12,7 +12,7 @@ app = Flask(__name__)
 CORS(app, resources={r"/*": {"origins": "http://localhost:5173"}})
 
 # Global State
-posts_df = pd.read_json('posts_test.jsonl', lines=True)
+posts_df = pd.read_json('posts.jsonl', lines=True)
 with open("topic_buckets.json", "r", encoding="utf-8") as f:
     domain_topics = json.load(f)
 stat_obj = StatGen(posts_df, domain_topics)

server/nlp.py

@@ -63,7 +63,7 @@ class NLP:
     def _get_topic_model(cls, device_str: str) -> SentenceTransformer:
         model = cls._topic_models.get(device_str)
         if model is None:
-            model = SentenceTransformer("all-mpnet-base-v2", device=device_str)
+            model = SentenceTransformer("all-MiniLM-L6-v2", device=device_str)
             cls._topic_models[device_str] = model
         return model